What is corruption?

Corruption is variously defined, but involves uses of power and/or money to achieve a desired but unethical and illegal (or at least extralegal) benefit. By its nature it involves someone in a position of authority seeking or able to confer the illicit benefit. As such it is not one thing but a range of practices that can occur in many contexts.

The simplest distinction is between a person in authority charging a fee or gift for a good or service that should be provided without charge, and a transaction between a private citizen and a person in authority to allow the former to get away with something unlawful (e.g., illegal goods, avoiding taxes or fines). One can also distinguish for example petty corruption (what an individual might encounter) from grand corruption (of the big money sort one might read about in the press), or systemic corruption (which is generalized and organized) from sporadic corruption (which may arise in diverse situations).

In fact, once one begins to consider details of specific situations, the taxonomy of corruption gets a lot more complex. Two organizations concerned with corruption offer glossaries of its various forms:

Personally, having encountered corruption (mostly indirectly) in West Africa at various points over the last three decades, and trying to make sense of those experiences and qualitative data from research by the project with which I worked, I have found J-P. Olivier de Sardan‘s discussions of what he calls the “corruption complex” helpful (see for example “A Moral Economy of Corruption in Africa?“).

Part of the reason I posted on the long-tail concept is that I believe it will be useful in various ways to analyzing the situation of less widely-spoken languages (LWSLs; previously I’ve used MINELs which says less about the size of the speaking community). I deliberately framed it in the context of the economics of language because I see the long tail as a model useful in the broader context of that field. In any event, we’re just beginning to explore this and it would be of interest to know of other efforts.

A clarification also needs to be made between what I’m seeing as two dynamics in the long tail of languages. Dan writes (referring to a previous Wikinomics posting that I referenced):

As Paul highlights in his post there are several tools and applications that, in theory, faciliate learning, or given Don’s take, not leaving, the long-tail.

It seems to me that these are really two different, although related, things. On the one hand, Paul looked more at how the potential “consumer” of language learning would perceive minority languages. On the other hand, I’m mostly interested in the view from the points of view closer to where the language is spoken, from individuals, households and communities who speak the language, to regional and national entities that serve them – govt., business, NGOs, education. The latter are all a different kind of “consumer” than potential language learners. (Parenthetically, I think this difference reflects one that I’ve noted in events related to the International Year of Languages: some people and organizations are focusing more on language learning and others more on a nexus of issues relating to language rights, endangered languages, etc.)

All of these viewpoints are valid, of course, but when considering language development and indeed survival it is useful to know whether ICT’s effect of lowering barriers for doing various things in/for less widely-spoken languages down the long tail ultimately balances or outweighs other factors that either encourage speakers of less-widely spoken languages to focus uniquely on more widely-spoken languages at the head of the distribution. Which is to say in effect, that the long-tail effect makes production and use of content and products in a language somewhere down the tail – say Soninke (language spoken by about a million people in Mali, Senegal & Mauritania, which has a historical link to the Ghana empire) – easier and cheaper for Soninke speakers than it was previously. But how will this affect use and development of the language?

In his Wikinomics blog article, Dan is skeptical, posing the question this way:

… in a world where the language of economics is conducted in one, perhaps two, and in the future maybe three languages, can a combination of technology, ethno-nationalism and culture trump trade and economics?

I’m not sure we can answer either question but it might help to look at the long tail in different ways to see what’s involved. In his book, The Long Tail, Chris Anderson shows that if you zero in on a section of the long tail, you find … another long tail distribution (see p. 21). One could for instance do the same with languages based on population of speakers, or, to consider the viewpoint from a country and its citizens, look at just the languages in that country. For example, the following graph uses figures from Ethnologue of first language (L1) speakers of languages of Mali :

This is another classic long-tail distribution. I’ve used color codes for very closely related tongues that are interintelligible (at least to some degree – this is a question that could be discussed at length another time). For instance, dark blue is used for the Manding tongues like Bambara, Jula, Malinke and Khassonke. The red color is for languages not in one of those groups. Soninke (snk) is one of these, with 700,000 speakers and 1 million or so overall – pretty significant in a particular region and fourth among the language categories Ethnologue lists for Mali.

Of course, in a multilingual societies people generally learn other languages no matter where their mother tongue may be in the distribution. So it makes more sense in terms of usage to plot out first & second (or additional) language speakers. In the following graph I plot out the combined figures for the closely related groups – whether they be called “language,” “macrolanguage,” or language cluster – and add estimated second language (L2) speakers above those:

There is some uncertainty about L2 speakership – estimates about the percentage of Mali’s 10+ million population that speak Bambara run from 65-80%; and for the official language of French, one probably low estimate is 15%. Fulfulde has historically been a lingua franca in central Mali.

And there are other ways we could graph out long tails of language as well. For instance on more local levels. Or, since there is a lot of trade and movement among countries of the West Africa region of which Mali is a part, and many of the language communities are divided by borders, one could do regional or subregional graphs.

What is the point? First, the dominant “two or three” languages when you narrow the geographical scale are not necessarily – and in fact usually are not – the same as one sees on the international level. English, Mandarin Chinese and Spanish may be the most significant worldwide, but none of them are major in Mali for instance. And languages that are relatively far down the tail in the international distribution may be at the top on a country or regional scale. Some languages specific to a country or region have some significant advantages in this context. And indeed, locally dominant languages do displace weaker languages to some degree. This may be the case with Bambara in Mali, or at least in much of the country, for instance.

Second, a language like Soninke which is pretty far down the tail in the international scale, has a higher profile nationally or subregionally (remembering it is a cross-border language).

The global distribution hides these realities. While it is true I think that the long-tail effect of advances in ICT generally lower the barriers and increase the potential for various kinds of work with LWSLs way down the tail (to the point where the main problems encountered are when the languages have few resources) – including for language learners (among whom the particular category of “heritage language learners” deserves special note) – it may be that the long tail distributions on more local levels are more informative for discussions of linguistic situations and language policy.

In other words, the significance of ICT’s effect on the potential to do various work (like publishing) in LWSLs may best be seen in reference to long tail distributions on country and regional levels.

Dan suggests that

As countries migrate through the demographic transition, and subsequently become increasingly urbanized, there’s an inherent move towards common languages in order to faciliate the trade of services and goods.

Whether this means more a “trimming” of the tail or more an evolution of the language portfolios of multilingual speakers and communities is open to discussion. None of us are suggesting that speakers of LWSLs should abandon their languages in favor of languages of wider communication (LWCs), but the question is whether a combination of application of ICTs and good language and education policies can facilitate people keeping and developing their languages, even if their numbers be few.

“The economics of language has been neglected and deserves much greater attention,” wrote economist Donald Lamberton in a book he edited in 2002. That may not have been too much of a revelation at the time – only a few years earlier (1994) another economist, François Grin, wrote that this field was tolerated “as an intriguing fringe interest” by the discipline of economics. I’d like to briefly explore an intriguing idea on the fringe of that fringe: whether there are or could be “long-tail” dynamics that give some advantages to minority languages.

But first, what is “economics of language”? Grin, in the same article mentioned above defined it as covering the study of:

…the effects of language on income (possibly revealing the presence of language-based discrimination), language learning by immigrants, patterns of language maintenance and spread in multilingual polities or between trading partners, minority language protection and promotion, the selection and design of language policies, language use in the workplace, and market equilibrium for language-specific goods and services.

Actually some of these issues are getting increased attention (another book on the topic was just published last year by Barry R. Chiswick and Paul W. Miller, for instance), so I suspect that economics of language is becoming a little more mainstream. (A good online review of the subject under the title “The Economics of Multilingualism” was written by Grin and François Vaillancourt.)

What does the “long tail” have to do with any of this? Well to begin with, the distribution of languages by number of speakers, if plotted out on a graph like the figure (from the Wikimedia Commons) to the right, is a long tail distribution. The question is whether this means anything with regard to the economics of languages – and in particular for minority or less-widely spoken languages (the ones I’ve liked to call MINELs) which are in the long tail.

By way of explanation, the “long tail” refers to a distribution where a few categories have a lot of each (they would be the green-shaded area in the figure), and many categories have progressively fewer (the yellow-shaded part). It was popularized by Chris Anderson in a 2004 article, and then a 2006 book, on new marketing strategies facilitated by the internet. As such, it is a kind of economic model.

How do languages fit this pattern? I plotted out a bar graph for the 50 languages with the most mother tongue speakers using figures from Wikipedia (originally from Ethnologue) and an online utility at Shodor.org.It’s “quick and dirty” but gives an idea of how the actual distribution compares to the long tail model. Needless to say, there is a very long and low “tail” to the right in this distribution after the first 50 languages.

I got the idea of connecting the long tail concept with languages from Laurent Elder of IDRC. When I finally got to read up on the subject it began to make sense. At least partway…

I have been among those suggesting that information and communication technologies make a lot of things possible or less expensive for MINELs that were impossible or too costly before. Desktop publishing or using webpages reduces barriers to producing and sharing text in any language – critical for languages with few resources and examples of a long tail effect. Cheaper communications via VOIP and expanded availability of cellphones facilitate dispersed member of a minority language community being able to speak their languages with each other. Community radio (a new use of an old technology) opens new ways of using the oral language. And so on. To be sure, dominant languages can use the same technologies, but the real advantage I think is for the non-dominant languages.

On the other hand – and here the application of the long-tail concept to language runs into problems perhaps similar to other attempts to apply economic analysis to languages – people don’t move “down the tail” to niche markets with language in the way they might with music or books (two of the prominent examples in Anderson’s writing on the subject). With language, the most prominent fact is that people live in the long tail, as it were, and there are some incentives to move up the tail to dominant languages. Part of the issue is how the new technologies facilitate not abandoning the linguistic home in the long tail when dominant languages are learned and used. Most people after all learn more than one language.

In any event, the long tail seems to be a useful concept in looking at the present and future of world languages. When I did a little research on this last fall, I came across an article on the Wikinomics blog that looked at the distribution of languages on the internet and posed questions re language learning. In other words, is there a long tail market for language services (mainly language learning)? This is a different take than mine above but also interesting. There may yet be others and perhaps, as the field of economics of language develops, more ambitious applications of the concept.